Development and Evaluation of a Low-Drift Inertial Sensor-Based System for Analysis of Alpine Skiing Performance
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AuthorRuiz García, Isidoro; Navarro Marchal, Ismael; Ocaña Wilhelmi, Francisco Javier; Palma López, Alberto José; Gómez López, Pablo Jesús; Carvajal Rodríguez, Miguel Ángel
Inertial sensorAccelerometerKinematicsAlpine skiingKineticsPhotogrammetry 3D
Ruiz-García, I.; Navarro-Marchal, I.; Ocaña-Wilhelmi, J.; Palma, A.J.; Gómez-López, P.J.; Carvajal, M.A. Development and Evaluation of a Low-Drift Inertial Sensor-Based System for Analysis of Alpine Skiing Performance. Sensors 2021, 21, 2480. [https://doi.org/10.3390/s21072480]
SponsorshipJunta de Andalucia European Commission B-TIC-468UGR18; European Commission
In skiing it is important to know how the skier accelerates and inclines the skis during the turn to avoid injuries and improve technique. The purpose of this pilot study with three participants was to develop and evaluate a compact, wireless, and low-cost system for detecting the inclination and acceleration of skis in the field based on inertial measurement units (IMU). To that end, a commercial IMU board was placed on each ski behind the skier boot. With the use of an attitude and heading reference system algorithm included in the sensor board, the orientation and attitude data of the skis were obtained (roll, pitch, and yaw) by IMU sensor data fusion. Results demonstrate that the proposed IMU-based system can provide reliable low-drifted data up to 11 min of continuous usage in the worst case. Inertial angle data from the IMU-based system were compared with the data collected by a video-based 3D-kinematic reference system to evaluate its operation in terms of data correlation and system performance. Correlation coefficients between 0.889 (roll) and 0.991 (yaw) were obtained. Mean biases from -1.13 degrees (roll) to 0.44 degrees (yaw) and 95% limits of agreements from 2.87 degrees (yaw) to 6.27 degrees (roll) were calculated for the 1-min trials. Although low mean biases were achieved, some limitations arose in the system precision for pitch and roll estimations that could be due to the low sampling rate allowed by the sensor data fusion algorithm and the initial zeroing of the gyroscope.